class_docstr: Translates node positions by randomly sampled translation values
  within a given interval (functional name: :obj:`random_jitter`).
  In contrast to other random transformations,
  translation is applied separately at each position.
  
  Args:
      translate (sequence or float or int): Maximum translation in each
          dimension, defining the range
          :math:`(-\mathrm{translate}, +\mathrm{translate})` to sample from.
          If :obj:`translate` is a number instead of a sequence, the same
          range is used for each dimension.
code: def __init__(
      self,
      translate: Union[float, int, Sequence[Union[float, int]]],
  ) -> None:
      self.translate = translate
  
file_path: pytorch_geometric/torch_geometric/transforms/random_jitter.py
imports: from itertools import repeat
  from typing import Sequence, Union
  from torch_geometric.data import Data
  from torch_geometric.data.datapipes import functional_transform
  from torch_geometric.transforms import BaseTransform
label_desc: Use image node_id 1 to create a new RandomJitter object from inherited base classes: BaseTransform with example: obj = RandomJitter(translate)